-The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R 2 =0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).
Rapid and early detection of Fire Blight as the most destructive bacterial disease of apple and pear trees is very important to avoid product loss. The objective of this research was to evaluate the usefulness of visible near-infrared spectrometry for early detection of Fire Blight. Three kinds of samples were selected: healthy leaves (H) from healthy trees and symptomatic (S) and non-symptomatic diseased (MS) leaves from infected trees. For spectral analysis, different preprocessing and processing techniques were carried out. Linear discriminant analysis, quadratic discriminant analysis, Mahalanobis discriminant analysis, soft independent modeling of class analogy (SIMCA) and partial least square-discrimination analysis were applied as classification techniques. Laboratory test by selective culture method was used to detect bacteria. Based on analyses, hyperspectral wavelengths for detection of H, MS and S leaves were obtained. SIMCA proved to be the strongest among all classifiers to discriminate healthy leaves from diseased leaves. The results indicated that structure intensive pigment index and modified simple ratio were sensitive to discriminate H-S, H-MS and S-MS leaves. Randomized difference vegetation index showed potential to classify H-S and S-MS samples. Anthocyanin reflectance index showed potential to discriminate H-MS samples. Finally, modified triangular vegetation index1 and modified chlorophyll absorption ratio index1 were identified and considered as spectral indices to discriminate S-MS samples. Based on these results, this technique is reliable for detecting non-symptomatic diseased leaves and is capable of early detection of Fire Blight before spreading.
Bacille Calmette-Guérin (BCG) vaccine has been globally used to protect infants against tuberculosis (TB) for about a century. This vaccine has been shown to provide some degree of non-specific protection from other respiratory tract infections. This advantage has encouraged researchers to investigate the potential protection of this vaccine from the coronavirus disease 2019 from different perspectives in the ongoing pandemic. In this study, we have comprehensively reviewed the latest articles on potential vaccine effectiveness of BCG on COVID-19 and summarized the possible impacts of the BCG against SARS-COV-2 in detail.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.